A neural network and heuristics hybrid strategy for job-shop scheduling problem
| dc.cclicence | N/A | en |
| dc.contributor.author | Yang, Shengxiang | |
| dc.contributor.author | Wang, Dingwei | |
| dc.date.acceptance | 1998-09 | |
| dc.date.accessioned | 2020-05-19T14:14:21Z | |
| dc.date.available | 2020-05-19T14:14:21Z | |
| dc.date.issued | 1999-06 | |
| dc.description | The file attached to this record is the author's final peer reviewed version. | en |
| dc.description.abstract | A new efficient neural network and heuristics hybrid strategy for job-shop scheduling is presented. The neural network has the property of adapting its connection weights and biases of neural units while solving feasible solution. Heuristics are used to accelerate the solving process of neural network and guarantee its convergence, and to obtain non-schedule schedule from solved feasible solution by neural network with orders of operations determined and unchanged. Computer simulations have shown that the proposed hybrid strategy is of high speed and excellent efficiency. | en |
| dc.funder | Other external funder (please detail below) | en |
| dc.funder.other | National Natural Science Foundation of China | en |
| dc.identifier.citation | Yang, S. and Wang, D. (1999) A neural network and heuristics hybrid strategy for job-shop scheduling problem. Journal of Systems Engineering, 14(2), pp.140-144. | en |
| dc.identifier.uri | https://dora.dmu.ac.uk/handle/2086/19616 | |
| dc.language.iso | zh | en |
| dc.peerreviewed | Yes | en |
| dc.projectid | 69684005 | en |
| dc.researchinstitute | Institute of Artificial Intelligence (IAI) | en |
| dc.subject | Job-shop scheduling | en |
| dc.subject | Neural network | en |
| dc.subject | Heuristics | en |
| dc.subject | Hybrid strategy | en |
| dc.title | A neural network and heuristics hybrid strategy for job-shop scheduling problem | en |
| dc.type | Article | en |